Developments in Algorithms for Sequence Alignment: A Review

The continuous development of sequencing technologies has enabled researchers to obtain large amounts of biological sequence data, and this has resulted in increasing demands for software that can perform sequence alignment fast and accurately. A number of algorithms and tools for sequence alignment...

Descripción completa

Detalles Bibliográficos
Autores principales: Chao, Jiannan, Tang, Furong, Xu, Lei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Review
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9024764/
https://www.ncbi.nlm.nih.gov/pubmed/35454135
http://dx.doi.org/10.3390/biom12040546
_version_ 1784690686435524608
author Chao, Jiannan
Tang, Furong
Xu, Lei
author_facet Chao, Jiannan
Tang, Furong
Xu, Lei
author_sort Chao, Jiannan
collection PubMed
description The continuous development of sequencing technologies has enabled researchers to obtain large amounts of biological sequence data, and this has resulted in increasing demands for software that can perform sequence alignment fast and accurately. A number of algorithms and tools for sequence alignment have been designed to meet the various needs of biologists. Here, the ideas that prevail in the research of sequence alignment and some quality estimation methods for multiple sequence alignment tools are summarized.
format Online
Article
Text
id pubmed-9024764
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-90247642022-04-23 Developments in Algorithms for Sequence Alignment: A Review Chao, Jiannan Tang, Furong Xu, Lei Biomolecules Review The continuous development of sequencing technologies has enabled researchers to obtain large amounts of biological sequence data, and this has resulted in increasing demands for software that can perform sequence alignment fast and accurately. A number of algorithms and tools for sequence alignment have been designed to meet the various needs of biologists. Here, the ideas that prevail in the research of sequence alignment and some quality estimation methods for multiple sequence alignment tools are summarized. MDPI 2022-04-06 /pmc/articles/PMC9024764/ /pubmed/35454135 http://dx.doi.org/10.3390/biom12040546 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Chao, Jiannan
Tang, Furong
Xu, Lei
Developments in Algorithms for Sequence Alignment: A Review
title Developments in Algorithms for Sequence Alignment: A Review
title_full Developments in Algorithms for Sequence Alignment: A Review
title_fullStr Developments in Algorithms for Sequence Alignment: A Review
title_full_unstemmed Developments in Algorithms for Sequence Alignment: A Review
title_short Developments in Algorithms for Sequence Alignment: A Review
title_sort developments in algorithms for sequence alignment: a review
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9024764/
https://www.ncbi.nlm.nih.gov/pubmed/35454135
http://dx.doi.org/10.3390/biom12040546
work_keys_str_mv AT chaojiannan developmentsinalgorithmsforsequencealignmentareview
AT tangfurong developmentsinalgorithmsforsequencealignmentareview
AT xulei developmentsinalgorithmsforsequencealignmentareview

Ejemplares similares